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Chapter 16 Electrophysiology
Published in B H Brown, R H Smallwood, D C Barber, P V Lawford, D R Hose, Medical Physics and Biomedical Engineering, 2017
Neurology is the branch of medicine dealing with all aspects of the nervous system. At least two types of electrophysiological measurement are usually made in a department of neurology; these are electroencephalography (EEG) and electromyography (EMG). EEG measurements can help in the diagnosis of epilepsy and are also useful in the investigation of brain tumours and accidental damage to the brain. EMG is usually taken to include both the recording of electrical signals from muscle and also the measurement of neural function using techniques such as nerve conduction measurement. EMG measurement is used in the diagnosis of muscle disease such as muscular dystrophy and also in the investigation of nerve damage which has resulted either from disease or physical injury.
Bridging Fashion Design and Color Effects
Published in Marcelo M. Soares, Francisco Rebelo, Ergonomics in Design Methods & Techniques, 2016
An understanding of the brain and nervous system functions is important in the overall understanding of color. It is intended to underline the involved key process within sight and brain. Neurology is the study of the nervous system, particularly with regard to humans. This field is meaningful for the study of color since it allows an understanding (as far as medical science allows) of the process involved between the arrival of the light wave and the physical reactions which result inside the human body.
Role of High-Performance VLSI in the Advancement of Healthcare Systems
Published in Balwinder Raj, Brij B. Gupta, Jeetendra Singh, Advanced Circuits and Systems for Healthcare and Security Applications, 2023
Jeetendra Singh, Balwant Raj, Monirujjaman Khan
Neurology is the medical field concerned with the detection and therapy of ailments of the nervous system, which includes the brain, nerves, and spinal cord. There are more than 600 diseases of the nervous system, which include brain tumors, epilepsy, and Parkinson's disease. Artificial neural networks (ANNs) are computing systems virtually stimulated by the biological neurons that constitute animal brains. Such systems learn to accomplish a task without being automated with particular rules. An ANN uses the processing of the brain as a valid point to build algorithms that can be used to guide complex patterns and prediction problems. An ANN considers data samples rather than the entire data set for any solution that in turn saves money and time. ANNs are networks of computing elements that have the capacity to respond to input stimuli and generate the desired output during VLSI design of neural networks [22,23]. Analog hardware needs to take care with respect to some key aspects: substrate-noise, variations in power supply, drift, leakage, etc. But analog VLSI implementation of ANN by means of a back-propagation algorithm diminishes cost and power dissipation. In order to minimize the power consumption, analog feed-forward neural networks are to be considered for solving the classification problems very easily [24,25]. Digital neural networks are almost produced automatically from a logic description of their functions. Digital ones are well acquainted with new processes and hence redesigning is not required. With these new processes, power and area are lessened in order to make the digital circuits optimized [26,27]. Digital neural networks are highly opted for classification problems even it is with or without analog-digital (AD) conversion of input signals. And moreover, digital networks surpass analog networks when it comes with or without an ADC [28].
AI-CDSS Design Guidelines and Practice Verification
Published in International Journal of Human–Computer Interaction, 2023
Xin He, Xi Zheng, Huiyuan Ding, Yixuan Liu, Hongling Zhu
Two-thirds of the participants were male (n = 4), and one-third were female (n = 2). The participants’ clinical practice experience ranged from 4 to 13 years, with a mean of 7.6 years. They had undergraduate (n = 4), graduate (n = 1), and doctoral degrees (n = 1). Four of them were attending physicians, one was a resident physician, and one was a chief assistant physician. As thrombolysis is mainly used for stroke patients, most participants were from the Neurology Department (n = 5), and one was from the Cardiology Department., All participants had experience in stroke diagnosis and thrombolytic therapy, ranging from one to 42 cases, with a mean of 18.8 instances. Interviews with participants lasted an average of 65.9 min, ranging from 50.8 min to 94.2 min. Each received a labor fee after the meeting to reward the physicians who participated despite their busy schedules.
Physician scheduling for emergency telemedicine across multiple facilities
Published in IISE Transactions on Healthcare Systems Engineering, 2023
Oluwasegun G. Olanrewaju, Murat Erkoc
Telemedicine is a new and fast-growing research area with limited research methodology in relation to physician scheduling. In this stream of research, Erdogan et al. (2018) focus on the optimal scheduling of telemedicine patients by presenting a two-stage stochastic linear program model considering rural areas. Rajan et al. (2019) investigate the impact of telemedicine technology of patient utility in a smaller population and the tradeoff between revenue maximization and welfare maximization. Wang et al. (2021) investigate how optimal price and capacity decision affect a nonprofit general hospital and a for-profit telemedicine firm while considering the patients waiting times and welfare. Ward et al. (2015) present a systematic review of telemedicine applications for hospital-based emergency care, which aims to synthesize the existing evidence on the impact of tele-emergency applications that could inform future efforts and research in this area. They report positive findings especially in terms of technical quality and user satisfaction, clinical processes and outcomes, throughput, and disposition, but the rigor of studies using these measures are limited. Kumar et al. (2020) present a forecasting model to predict consultation demand of tele-neurology (stroke) cases to optimize telemedicine provider staffing.
Rehabilitation robotics after stroke: a bibliometric literature review
Published in Expert Review of Medical Devices, 2022
Giacomo Zuccon, Basilio Lenzo, Matteo Bottin, Giulio Rosati
As shown in Figure 2(a), the top five journals in order of publication number are Journal of NeuroEngineering and Rehabilitation with a total of 269 papers, followed by IEEE Transactions on Neural Systems and Rehabilitation Engineering with 205 papers, Neurorehabilitation and Neural Repair with 72 papers, Archives of Physical Medicine and Rehabilitation with 61 papers, and NeuroRehabilitation with 60 papers (the acronyms used for the journals are given in Table 1). This ranking includes the collection of all IEEE journals that do not match the selection criteria indicated above with a total number of papers equal to 124. The content of these journals is split over computer science applications, biomedical engineering, and medicine (neurology and rehabilitation). In the last four years, Journal of NeuroEngineering and Rehabilitation, IEEE Transactions on Neural Systems and Rehabilitation Engineering, and NeuroRehabilitation have continued to publish the most papers on post-stroke rehabilitation robotics, followed by Frontiers in Neuroscience and Frontiers in Neurology.